SECTION A: Basic Information
- Brief Introduction to the Module
As part I of dissertation training, this modular ALA intends to develop MSc students’ research skills. It aims at enhancing students’ understanding of different types of research methods and how to apply them appropriately. Quantitative research methods are supposed to be taught in an entry level in this module, including fundamental logics for quantitative research methods, data collection and statistical inference methods. This module is delivered online for Semester 2, 2020/21. A series of online lectures will be released to the students. Meanwhile, complementary materials and knowledge will be delivered to the students in online tutorials.
SECTION B: What you can expect from the module
- Educational Aims of the Module
As part I of dissertation training, this modular ALA intends to develop MSc students’ research skills. It aims at enhancing students’ understanding of different types of research methods and how to apply them appropriately.
- Learning Outcomes
- Identify a problem and provide viable solutions.
- Demonstrate the ability to handle data collection and analysis.
- Explain, discuss and give concluding statements based on data analysis results.
- Communicate data analysis results effectively
- Assessment Details
In this module, you are required to submit a short research paper as an individual assignment [CW].
GENERAL INSTRUCTIONS TO CANDIDATES:
- The report should be written in English.
- Please use the cover sheet and report template in ICE to produce your report.
- An electronic version of the report [in MS Word] should be submitted through the LMO The electronic file name should be “Module number + Your student ID + Your surname + Individual Assignment
+ 202122 S1”.
For example: BUS901-000000-Bob-Individual Assignment-202122 S1.
- Standard penalties apply for lateness and plagiarism. Please note that weekends are treated as normal working days and count towards the lateness.
Select one problem/topic and use the methods covered in this module to write a research essay. The methods can be included but not limited to the methods as below:
- Hypothesis tests on mean and variance;
- Analysis of Variance [ANOVA].
- Linear regression.
Detailed requirements on this report can be found in the next page. Linear programming;
You are supposed to write this essay by yourself alone. Your assignment markings are graded based on the below items.
|Marking Item||Assessor||Marking Weight|
|Problem/topic statement.||Module leader||10%|
|Literature review.||Module leader||20%|
|Analysis methodology.||Module leader||30%|
|Results of analysis.||Module leader||20%|
GENERAL GUIDELINES FOR REPORT:
There is not requirement for word limit of the essay and the essay is not supposed to reach the level of a formal research paper or even a dissertation. Just consider this to be a simple practice of your future research.
On the cover page of your report, please write down all the information required.
In the problem/topic statement section, please give a brief description of the problem/topic you concern in this essay, including a general scope of the topic, the importance of the topic and which areas can the topic contribute to.
In the literature review section, please give a comprehensive review of related work on the same area you concern. Try to highlight some of the papers that have a higher significance or a closer relation with your work. Then, you should make a brief discussion of the existing drawbacks potential improvements of the research on this topic and associate your contribution in this work with these issues.
In the methodology section, please explain in details the approaches involved, including data collection and analysis techniques you use. In particular, I require you to follow the “principle first” rule, which means before you introduce a definition, index, theory, method, you should make a brief interpretation of the reason you need it.
In the results section, please provide the detailed results and findings through your methodology, also draw some implications and/or commentary to support your conclusion. You may use actual data set that you collect from real sources. Or, you may use artificial data generated by any software. But please be noted that your results must be consistent with your data set and analysis process.
In the conclusion section, summarize your problem/topic, the methodology you use, the conclusion you draw about the topic and your recommendations to the other researchers concerning the same topic [any potential future research direction, etc.].
In the References section, please list all the references you have cited for your report in an alphabetical order using the APA or Vancouver style [author-year]. Please arrange all references in the right format.
Lai and Robbins  [In the main body]
Lai, T. L. and Robbins, H. , “Asymptotically efficient adaptive allocation rules,” Advances in Applied Mathematics, 6, 4–22.
Please be noted that the opportunity for the re-sitting of an assessment is not available.
Coursework must be submitted through the submission link on LMO no later than 8:00 pm on the following date: 31/December/2021
If more details are specified for the assessment, you are referred to the students to Assessment policy on E-bridge or further notice on Learning Mall Online.
- Methods of Learning and Teaching
Main delivery approach is seminar with different focuses on each seminar. Students will be guided by each seminar topic to start their dissertation prep at an early stage. This also links to the delivery of BUS902 in semester 2, but two modules are comparatively independent.
- Reading Materials
Mandatory textbook is a required book in either print or electronic format for a module that students are obligated to purchase.
Optional textbook is a book in print that students can choose to purchase or not.
Reference textbook is a book in print that is considered additional or recommended reading by academic staff and is only purchased for Library’s collection where it can be offered for loan.